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Browse 6,842 models across providers, modalities, and use cases.
🌐 All Models
6,842 models · Page 175 of 191
Mixtral 8×7B Instruct on DeepInfra — popular MoE model with 32K context and strong multilingual performance.
Wan-AI/Wan2.7-Image-Edit — served on DeepInfra's GPU cloud for scalable, cost-efficient inference.
Bria/gen_fill — served on DeepInfra's GPU cloud for scalable, cost-efficient inference.
DeepSeek V3 — 671B MoE model with exceptional coding and math performance at very low cost.
Cohere's multilingual embeddings supporting 100+ languages for global semantic search.
gpt-oss-120b is an open-weight, 117B-parameter Mixture-of-Experts (MoE) language model from OpenAI designed for high-reasoning, agentic, and general-purpose production use cases. It activates 5.1B parameters per forward pass and is optimized...
Qwen3-VL-30B-A3B-Instruct is a multimodal model that unifies strong text generation with visual understanding for images and videos. Its Instruct variant optimizes instruction-following for general multimodal tasks. It excels in perception...
Microsoft Phi-4 14B — small language model achieving state-of-the-art results on reasoning tasks.
Qwen3-14B is a dense 14.8B parameter causal language model from the Qwen3 series, designed for both complex reasoning and efficient dialogue. It supports seamless switching between a "thinking" mode for...
Qwen3-235B-A22B-Thinking-2507 is a high-performance, open-weight Mixture-of-Experts (MoE) language model optimized for complex reasoning tasks. It activates 22B of its 235B parameters per forward pass and natively supports up to 262,144...
Meta Llama 3.1 8B Instruct on DeepInfra — fast, affordable open-source model with 128K context.
Gemma 3 introduces multimodality, supporting vision-language input and text outputs. It handles context windows up to 128k tokens, understands over 140 languages, and offers improved math, reasoning, and chat capabilities,...
Qwen3-Max-Thinking is the flagship reasoning model in the Qwen3 series, designed for high-stakes cognitive tasks that require deep, multi-step reasoning. By significantly scaling model capacity and reinforcement learning compute, it...